BOOK OF ABSTRACTS ADDRESSING CHALLENGES IN APPLIED MECHANICS THROUGH ARTIFICIAL INTELLIGENCE APPLICATIONS
Bibliographic record
Abstract
PREFACE It is our great honor and pleasure to welcome you to the 650th EUROMECH Colloquium, entitled "Addressing Challenges in Applied Mechanics through Artificial Intelligence Applications", held in Belgrade, Serbia, from August 27 to 29, 2025. This Colloquium marks a significant milestone, the first-ever EUROMECH event organized in our region and as such, represents a unique opportunity to set the stage for future scientific developments at the intersection of applied mechanics and artificial intelligence. The Colloquium brings together distinguished experts and early-career researchers from over fifteen countries, including Austria, Bosnia and Herzegovina, Bulgaria, Canada, China, the Czech Republic, Germany, Greece, Hungary, Iceland, North Macedonia, Poland, Slovenia, the United Kingdom, the United States and others. This international participation fosters a vibrant and collaborative atmosphere for scientific exchange and innovation. ...
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".